The relationship between sleep pattern and depression in Chinese shift workers: A mediating role of emotional exhaustion

Abstract

Objectives: To explore the relationship between sleep pattern (morningnesseveningness) and depression in Chinese shift workers ("Three Shifts" workers), and to examine whether emotional exhaustion plays a mediating role in this relationship. Study Design: We examined the impact of sleep pattern on the depression of three shifts workers, focusing on the mediating effect of emotional exhaustion. Methods: A total of 1303 shift workers in the north and south of China were invited to participate in this study using convenience sampling. They completed a questionnaire which collected information on socio-demographic variables, along with measures of sleep pattern, depression, and emotional exhaustion. Using structural equation modelling, the mediating role of emotional exhaustion in sleep pattern and depression was explored. Results: Of the three shifts workers 46.43% reported symptoms of depression; 27.84% identified as morning types while only 6.56% were evening types, with the remaining 65.60% falling into the intermediate category. There was a negative correlation between sleep pattern and depression, and between sleep pattern and emotional exhaustion, but a positive correlation between emotional exhaustion and depression. As predicted, emotional exhaustion played a mediating role in the relationship between sleep pattern and depression. Conclusions: Having an evening sleep pattern was a risk factor for depression in three shifts workers; however, emotional exhaustion mediated the relationship between sleep pattern and depression. This finding may inform interventions aimed at reducing the level of depression within three shifts staff.

The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support

“…Therefore, the relationship between AI application and employee depression here is more of a positive relationship formed by the opportunities brought by AI technology to employees’ career development. Second, emotional exhaustion plays a mediating role between AI awareness and employee depression, showing that the threat of AI technology to employees’ mental health mainly comes from the threat of AI changes to employee resources, which is consistent with the results of previous studies, showing that emotional exhaustion plays a mediating role in the process of stress factors and leads to employee depression [ 53 , 55 ]. In addition, when studying the impact of AI awareness on employees’ psychological state and work attitudes, Brougham and Haar posited that AI awareness was related to a series of negative consequences [ 7 ].…”

“…It is also found in studies on Chinese students that emotional exhaustion is positively related to depression [ 52 , 53 ]. Depressive disorders are also found to be positively predicted among teachers in primary and secondary schools as well as nurses with emotional exhaustion [ 54 , 55 ]. Therefore, we put forward hypothesis 3: emotional exhaustion will be positively associated with employee depression.…”

Association between nocturnal sleep duration and the risk of hyperuricemia among Chinese government employees: A cross-sectional study

“…Government employees have the characteristics of long working h and lack of physical activity, so they are more likely to suffer from diseases than ordinary people ( 26 , 27 ). Moreover, occupational staff have poorer sleep quality and shorter sleep duration ( 28 ).…”

Predicting Risk-Coping Behaviors In the Urban Relocation Process by Online Negative Emotions：A Case from Beijing

“…Lei and Yang (2016) proposed that stronger negative emotions correlate with higher likelihoods of choosing high-risk coping behaviors. Hu et al (2020) quantitatively established a positive correlation between risk perception, negative emotions, and rumor-spreading behavior, with negative emotions playing mediating roles. Despite evidence of negative emotions driving risk-coping behaviors, there is limited research exploring whether negative emotions can predict public risk-coping behaviors in urban relocation processes.…”